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Special Issue "Satellite Remote Sensing of Weather, Water and Climate Couplings and Phenomena"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: 31 August 2019.

Special Issue Editors

Guest Editor
Prof. Len Pietrafesa

Professor Emeritus, North Carolina State University, Raleigh, NC 27695, USA
Burroughs & Chapin Scholar, Coastal Carolina University, Conway, SC 29526, USA
Website | E-Mail
Interests: observations of and numerical modeling of atmospheric, oceanic, estuary, land and hydraulic inter-actively coupled systems; relationships between climate and weather coupled systems; wind-wave-current coupled interactions
Guest Editor
Dr. Francesco Bignami

Institute of Atmospheric Sciences and Climate, UOS Rome, 00133 Roma, Italy
Website | E-Mail
Phone: +39 06 4993 4634
Interests: theoretical aspects of physical oceanography; air-sea interaction; the impact of physical oceanographic factors on phytoplankton, zooplankton and pelagic fish dynamics and distribution
Guest Editor
Dr. Emanuele Böhm

Institute of Marine Sciences, UOS Rome, 00133 Roma, Italy
Website | E-Mail
Interests: satellite oceanography in conjunction with in situ observations
Guest Editor
Prof. Biao Zhang

Nanjing University of Information Science and Technology, Nanjing 210044, China
Website | E-Mail
Phone: +86 25 58695692
Interests: tropical cyclone remote sensing; marine dynamic envionment observation; air-sea interaction; marine and atmosphere mobile measuring technology
Guest Editor
Prof. Qing Xu

Hohai University, Nanjing 210098, China
Website | E-Mail
Interests: Ocean remote sensing

Special Issue Information

Dear Colleagues,

Satellite remote sensing presents a robust tool to address and unravel coupled weather, water and climate phenomena at multiple scales. The temporal and spatial scales of atmospheric, oceanic, and hydrologic environmental phenomena span the period range from isolated events, particularly extreme events, to that of sub-seasonal variability in the Earth’s interactively coupled atmospheric, oceanic, and hydrologic systems. There are significant associated implications for human and ecological systems and these have become an emerging topic around which issues of societal and economic value and sustainability can be examined and used for societal response and planning. In this issue, remote sensing tools comprehensively address these phenomena because of the incredible spatial synoptic coverage that they provide. Coupled with environmental observational data sets and mathematical modeling output, satellite remote sensing couples observed and/or modeled environmental processes to societal impacts. Moreover, satellite data used for numerical model validation, are now being assimilated into next-gen numerical modeling strategies, advancing event prognostications. Specific topics include coastal renewable energy assessment; storm induced coastal and inland flooding; flood hazard mapping; atmospheric coastal frontal system detection; African SAL detection; ocean heat content; multi-scale storm phenomena components; atmospheric rivers; and new uncharted uses of different types of remotely sensed imagery for pattern recognition.

Prof. Len Pietrafesa
Dr. Francesco Bignami
Dr. Emanuele Böhm
Prof. Biao Zhang

Prof. Qing Xu

Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (6 papers)

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Research

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Open AccessArticle
Multiple-Scale Variations of Sea Ice and Ocean Circulation in the Bering Sea Using Remote Sensing Observations and Numerical Modeling
Remote Sens. 2019, 11(12), 1484; https://doi.org/10.3390/rs11121484
Received: 21 May 2019 / Revised: 13 June 2019 / Accepted: 20 June 2019 / Published: 22 June 2019
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Abstract
The Bering Sea is located between the Aleutian Low and Siberian High, with strong seasonal variations in the oceanic circulation and the sea ice coverage. Within such a large-scale system, the physical processes in the Bering Sea carry interannual variability. The special topography [...] Read more.
The Bering Sea is located between the Aleutian Low and Siberian High, with strong seasonal variations in the oceanic circulation and the sea ice coverage. Within such a large-scale system, the physical processes in the Bering Sea carry interannual variability. The special topography in the Bering Sea traps a strong jet along the Bering Slope, whose instability enriches the eddy activity in the region. A Regional Oceanic Modeling System (ROMS), coupled with a sea ice module, is employed to study multiple-scale variability in the sea ice and oceanic circulation in the Bering Sea for interannual, seasonal, and intra-seasonal eddy variations. The model domain covers the whole Bering Sea and a part of the Chukchi Sea and south of Aleutian Islands, with an averaged spatial resolution of 5 km. The external forcings are momentum, heat, and freshwater flux at the surface and adaptive nudging to reanalysis fields at the boundaries. The oceanic model starts in an equilibrium state from a multiple year cyclical climatology run, and then it is integrated from years 1990 through 2004. The 15 year simulation is analyzed and assessed against the observational data. The model accurately reproduces the seasonal and interannual variations in the sea ice coverage compared with the satellite-observed sea ice data from the National Snow and Ice Data Center (NSIDC). Sea surface temperature and eddy kinetic energy patterns from the ROMS agree with satellite remote sensing data. The transportation through the Bering Strait is also comparable with the estimate of mooring data. The mechanism for seasonal and interannual variation in the Bering Sea is connected to the Siberia-Aleutian index. Eddy variation along the Bering Slope is discussed. The model also simulates polynya generation and evolution around the St. Lawrence Island. Full article
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Open AccessArticle
SST Anomalies in the Mozambique Channel Using Remote Sensing and Numerical Modeling Data
Remote Sens. 2019, 11(9), 1112; https://doi.org/10.3390/rs11091112
Received: 3 April 2019 / Revised: 4 May 2019 / Accepted: 7 May 2019 / Published: 9 May 2019
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Abstract
Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same [...] Read more.
Based on both satellite remote sensing sea surface temperature (SST) data and numerical model results, SST warming differences in the Mozambique Channel (MC) west of the Madagascar Island (MI) were found with respect to the SST east of the MI along the same latitude. The mean SST west of the MI is up to about 3.0 °C warmer than that east of the MI. The SST differences exist all year round and the maximum value appears in October. The area of the highest SST is located in the northern part of the MC. Potential factors causing the SST anomalies could be sea surface wind, heat flux and oceanic flow advection. The presence of the MI results in weakening wind in the MC and in turn causes weakening of the mixing in the upper oceans, thus the surface mixed layer depth becomes shallower. There is more precipitation on the east of the MI than that inside the MC because of the orographic effects. Different precipitation patterns and types of clouds result in different solar radiant heat fluxes across both sides of the MI. Warm water advected from the equatorial area also contribute to the SST warm anomalies. Full article
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Open AccessArticle
Estimation of Surface Air Specific Humidity and Air–Sea Latent Heat Flux Using FY-3C Microwave Observations
Remote Sens. 2019, 11(4), 466; https://doi.org/10.3390/rs11040466
Received: 21 January 2019 / Revised: 6 February 2019 / Accepted: 20 February 2019 / Published: 24 February 2019
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Abstract
Latent heat flux (LHF) plays an important role in the global hydrological cycle and is therefore necessary to understand global climate variability. It has been reported that the near-surface specific humidity is a major source of error for satellite-derived LHF. Here, a new [...] Read more.
Latent heat flux (LHF) plays an important role in the global hydrological cycle and is therefore necessary to understand global climate variability. It has been reported that the near-surface specific humidity is a major source of error for satellite-derived LHF. Here, a new empirical model relating multichannel brightness temperatures ( T B ) obtained from the Fengyun-3 (FY-3C) microwave radiometer and sea surface air specific humidity ( Q a ) is proposed. It is based on the relationship between T B , Q a , sea surface temperature (SST), and water vapor scale height. Compared with in situ data, the new satellite-derived Q a and LHF both exhibit better statistical results than previous estimates. For Q a , the bias, root mean square difference (RMSD), and the correlation coefficient (R2) between satellite and buoy in the mid-latitude region are 0.08 g/kg, 1.76 g/kg, and 0.92, respectively. For LHF, the bias, RMSD, and R2 are 2.40 W/m2, 34.24 W/m2, and 0.87, respectively. The satellite-derived Q a are also compared with National Oceanic and Atmospheric Administration (NOAA) Cooperative Institute for Research in Environmental Sciences (CIRES) humidity datasets, with a bias, RMSD, and R2 of 0.02 g/kg, 1.02 g/kg, and 0.98, respectively. The proposed method can also be extended in the future to observations from other space-borne microwave radiometers. Full article
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Open AccessArticle
Variability of the Great Whirl and Its Impacts on Atmospheric Processes
Remote Sens. 2019, 11(3), 322; https://doi.org/10.3390/rs11030322
Received: 28 December 2018 / Revised: 29 January 2019 / Accepted: 1 February 2019 / Published: 6 February 2019
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Abstract
Using satellite remote sensing data and re-analysis products for the period of 1993–2015, the variation of a large anticyclonic eddy, the so-called Great Whirl (GW), located in the Northwest Indian Ocean off the coast of Somali, and its impacts on atmosphere were investigated. [...] Read more.
Using satellite remote sensing data and re-analysis products for the period of 1993–2015, the variation of a large anticyclonic eddy, the so-called Great Whirl (GW), located in the Northwest Indian Ocean off the coast of Somali, and its impacts on atmosphere were investigated. The GW is generated in early summer and decays in late fall every year. The center of the GW is located at 7.73°N, 53.20°E. The mean lifetime, sea level anomaly (SLA) difference, sea surface temperature anomaly (SSTA), radius, normalized vorticity, eddy kinetic energy (EKE), and deformation rate are 169 days, 0.07 m, 0.83 °C, 116.86 km, −0.53, 0.08 m 2 · s 2 , and 0.58, respectively. All these variables exhibit interannual variations. Composite analyses show that the maximum values of sea surface temperature (SST), wind, and water vapor anomalies occur in the northwest of the GW center. The fitting coefficient between the SST and wind speed anomaly is 1.1, indicating that, corresponding to 1 °C increases of the SST, the wind speed increases by about 1.1 m · s 1 , and the fitting coefficient between the SST and water vapor anomaly is 0.45, indicating that water vapor increases by about 0.45 mm in response to 1 °C increases in the SST. In the vertical direction, the maximum and minimum values of vertical velocity anomalies and vertical transport of transient zonal momentum occur over the GW at about 900 hPa, and wind speed anomalies occur at about 950 hPa. Both the positive transport anomalies of transient zonal momentum and the positive vertical velocity anomalies on the west side of the GW can accelerate the wind speed in the lower level. Full article
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Other

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Open AccessLetter
Sea State Bias Variability in Satellite Altimetry Data
Remote Sens. 2019, 11(10), 1176; https://doi.org/10.3390/rs11101176
Received: 21 March 2019 / Revised: 20 April 2019 / Accepted: 7 May 2019 / Published: 17 May 2019
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Abstract
Sea State Bias (SSB) contributes to global mean sea level variability and it needs cm-level range adjustment due to the instrumental drift over time. To investigate its variations and correct the global and regional sea level trend precisely, we calculate the temporal and [...] Read more.
Sea State Bias (SSB) contributes to global mean sea level variability and it needs cm-level range adjustment due to the instrumental drift over time. To investigate its variations and correct the global and regional sea level trend precisely, we calculate the temporal and spatial variability of the SSB correction in TOPEX, Jason-1, Jason-2 and Jason-3 missions, separately, as well as in the combined missions over the period 1993–2017. The long-term trend in global mean operational 2D non-parametric SSB correction is about −0.03 ± 0.03 mm/yr, which accounts for 1% of current global mean sea level change rate during 1993–2016. This correction contributes to sea level change rates of −1.27 ± 0.21 mm/yr and −0.26 ± 0.13 mm/yr in TOPEX-A and Jason-2 missions, respectively. The global mean SSB varies up to 7–10 mm during the very strong ENSO events in 1997–1998 and 2015–2016. Furthermore, the TOPEX SSB trend, which is consistent with recently reported sea level trend drift during 1993–1998, may leak into the determined global sea level trend in the period. Moreover, the Jason-1/2 zonal SSB variability is highly correlated with the significant wave height (SWH). On zonal average, SSB correction causes about 1% uncertainty in mean sea level trend. At high SWH regions, the uncertainties grow to 2–4% near the 50°N and 60°S bands. This should be considered in the study of regional sea level variability. Full article
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Open AccessLetter
Impact of Cyclonic Ocean Eddies on Upper Ocean Thermodynamic Response to Typhoon Soudelor
Remote Sens. 2019, 11(8), 938; https://doi.org/10.3390/rs11080938
Received: 11 March 2019 / Revised: 11 April 2019 / Accepted: 15 April 2019 / Published: 18 April 2019
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Abstract
By using multiplatform satellite datasets, Argo observations and numerical model data, the upper ocean thermodynamic responses to Super Typhoon Soudelor are investigated with a focus on the impact of an ocean cyclonic eddy (CE). In addition to the significant surface cooling inside the [...] Read more.
By using multiplatform satellite datasets, Argo observations and numerical model data, the upper ocean thermodynamic responses to Super Typhoon Soudelor are investigated with a focus on the impact of an ocean cyclonic eddy (CE). In addition to the significant surface cooling inside the CE region, an abnormally large rising in subsurface temperature is observed. The maximum warming and heat content change (HCC) reach up to 4.37 °C and 1.73 GJ/m2, respectively. Moreover, the HCC is an order of magnitude larger than that calculated from statistical analysis of Argo profile data in the previous study which only considered the effects caused by typhoons. Meanwhile, the subsurface warming outside the CE is merely 1.74 °C with HCC of 0.39 GJ/m2. Previous studies suggested that typhoon-induced vertical mixing is the primary factor causing subsurface warming but these studies ignored an important mechanism related to the horizontal advection caused by the rotation and movement of mesoscale eddies. This study documents that the eddy-induced horizontal advection has a great impact on the upper ocean responses to typhoons. Therefore, the influence of eddies should be considered when studying the responses of upper ocean to typhoons with pre-existing mesoscale eddies. Full article
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